As I look at these results on talent, I see both how far we’ve come with AI and how much work is still to be done in some areas.
Five or so years ago, software engineering would not have been classified as the highest-priority AI role because many organizations focused on simply building discrete models as
they experimented with the technology. But as the business value became clear, organizations realized the need for insights from AI to be delivered into a front end where people can consume and apply them for impact. The hiring of machine learning (ML) engineers similarly shows the maturation of AI; businesses need this role now because they’re working to embed ML into systems regularly and reliably.
On the other hand, despite knowing for close to a decade about the growing need for roles like data scientists and data engineers, we still haven’t moved the needle enough on the supply side. Hiring from boot camps is picking up because experienced talent is just not available. It isn’t easy to set up learning pathways for this fresh talent, but organizations have little choice. Reskilling efforts are also a big undertaking, but it’s necessary to fill the gaps. To meet the need, we actually need many more organizations reskilling than what we’re seeing in these results.
The diversity figures are disappointing but sadly unsurprising. Data science is a team sport. Diverse perspectives are important. It has been shown time and again that bias issues will proliferate when organizations lack a diverse enough team to call out issues. And just like other research we’ve conducted has shown, diversity correlates with strong performance in addition to being the right thing to do. If not careful, with AI, lack of diversity can lead to distrust. Finally, it’s important to remember that these AI jobs are among some of the highest paid, and demand will only increase. We risk undermining the progress we’ve made to date on closing pay gaps for women and ethnic minorities if they are not equally represented in this high-demand skills base. We must continue to find ways to get more women and minorities engaged in STEM in their education years and beyond.
Helen Mayhew
McKinsey commentary
Partner, Sydney
